Identifying accurately significant changes in machine performance indicative of an occurred failure, a likely to occur failure, or a future failure (e.g., fault) is an important component of predictive maintenance. In some examples, more than 80% of all complex mechanical equipment can fail accidentally and without any relation to their life-cycle period. Conventional techniques for condition monitoring involve positioning one or more sensors at or near a machine. Each sensor can be configured to monitor one or more condition parameters of the machine. Critical to accurate machine condition monitoring is the reliability of the sensors themselves. For example, without sufficient energy, sensors would experience down-time or even failures, and may go unattended for substantial period of times, in some instances, years.